Fighting Fire with Better Data

Texas State University is using “smart city” ideas to help firefighters be more effective and efficient.

Texas State English Professor Aimee Roundtree is using text mining to analyze large volumes of fire department records to find patterns and insights that can make Texas communities safer.

Her work uses features of natural language processing, user testing and interviewing to better understand and even improve the ways people communicate.

Supported by a State Farm Insurance community grant, her research is helping San Marcos and College Station firefighters keep better records of their work.

Historically, there are inconsistencies in the quality of emergency incident reports. The very complicated code system that governs how first responders categorize incidents often invites problems — for example, using some codes (such as “public service” or “false alarms”) as catchalls for a wide variety of emergency situations.

This makes it difficult to track and identify potentially useful trends and information on fire risk.

“I think that it’s very important that our reporting be as accurate and reliable as possible,” Kuhlman said.

The project grew out of Roundtree’s participation in a National Science Foundation grant application to use big data solutions for improving first responder services in smaller cities and towns, including Austin.